The Zn2+-transporting Pathways in Pancreatic β-Cells
Bibliographic record
Abstract
In pancreatic beta-cells Zn(2+) is crucial for insulin biosynthesis and exocytosis. Despite this, little is known about mechanisms of Zn(2+) transport into beta-cells or the regulation and compartmentalization of Zn(2+) within this cell type. Evidence suggests that Zn(2+) in part enters neurons and myocytes through specific voltage-gated calcium channels (VGCC). Using a Zn(2+)-selective fluorescent dye with high affinity and quantum yield, FluoZin-3 AM and the plasma membrane potential dye DiBAC(4)(3) we applied fluorescent microscopy techniques for analysis of Zn(2+)-accumulating pathways in mouse islets, dispersed islet cells, and beta-cell lines (MIN6 and beta-TC6f7 cells). Because the stimulation of insulin secretion is associated with cell depolarization, Zn(2+) (5-10 mum) uptake was analyzed under basal (1 mm glucose) and stimulatory (10-20 mm glucose, tolbutamide, tetraethylammonium, and high K(+)) conditions. Under both basal and depolarized states, beta-cells were capable of Zn(2+) uptake, and switching from basal to depolarizing conditions resulted in a marked increase in the rate of Zn(2+) accumulation. Importantly, L-type VGCC (L-VGCC) blockers (verapamil, nitrendipine, and nifedipine) as well as nonspecific inhibitors of Ca(2+) channels, Gd(3+) and La(3+), inhibited Zn(2+) uptake in beta-cells under stimulatory conditions with little or no change in Zn(2+) accumulation under low glucose conditions. To determine the mechanism of VGCC-independent Zn(2+) uptake the expression of a number of ZIP family Zn(2+) transporter mRNAs in islets and beta-cells was investigated. In conclusion, we demonstrate for the first time that, in part, Zn(2+) transport into beta-cells takes place through the L-VGCC. Our investigation demonstrates direct Zn(2+) accumulation in insulin-secreting cells by two pathways and suggests that the rate of Zn(2+) transport across the plasma membrane is dependent upon the metabolic status of the cell.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".